基于定子磁链定向的异步电机无速度传感器矢量控制系统的仿真分析

本文介绍了一种基于定子磁链定向的异步电机无速度传感器矢量控制系统，推导出异步电机在定子磁链定向下的数学模型，并依此建立控制系统，最后给出了系统的仿真策略和调速性能的仿真结果。     

基于MRAS的异步电机无速度传感器的矢量控制

由于电机定转子参数的变化,利用一般的转子磁链对转速进行估算,将导致不能得到准确的结果。这里采用积分型转子磁链的参考和可调模型构建出一个基于MRAS的异步电机无速度传感器的矢量控制模型。该模型提高了矢量控制系统的动态性能并利用MATLAB,sIMULINK进行了异步电机无速度传感器矢量控制系统的仿真,验证了文中所采用的模型参考自适应的速度估算方法的可行性以及对参数误差的鲁棒性。     

基于MRAS的无速度传感器异步电机矢量控制研究

本文依据异步电机矢量控制的基本原理,构建了无速度传感器的矢量控制系统。该系统中采用了转子磁链观测器方法,并运用模型参考自适应法进行了转子速度的估计。文中通过了Matlab/Simulink构建系统仿真模型,结果表明了系统的正确性与可行性。     

基于定子磁链矢量预测的DTC系统研究

针对直接转矩控制(DTC)技术中采用的传统滞环控制存在转矩及电流脉动大,过电压扇区时磁链轨迹畸变的缺点,提出一种基于定子磁链矢量预测的直接转矩控制方法。首先,根据磁链和转矩的偏差,预测出下一个控制周期的磁链矢量;然后,用预测磁链矢量减去当前的磁链矢量,得到需要加在电机定子上的电压矢量,以补偿当前的偏差。通过仿真说明了改进的系统抑制了磁链和转矩脉动,改善了电流波形,抑制了谐波,具有较好的动静态性能。     

无速度传感器异步电机矢量控制研究

本文以异步电动机矢量控制原理为基础,研究基于MRAS的无速度传感器矢量控制系统。介绍一种改进型电压模型转子磁链观测方案,采用Matlab/Simulink软件进行了仿真实验。实验结果证明该方法能够较准确地估算转子磁链和转速,系统运行良好。     

双馈电机矢量控制系统的研究

论述了矢量控制技术,介绍了双馈电机按定子磁链定向矢量控制原理,构建了双馈电机矢量控制系统。对该系统进行了matlab仿真,仿真结果验证了模型的正确性。     

基于SVM-PWM的异步电动机直接转矩控制

文中介绍了空间矢量脉宽调制(SVM-PWM)的基本原理,构建了异步电动机直接转矩控制的模型,定子电压由空间矢量脉宽调制方式实现。通过MATLAB/Simulink对该系统进行了仿真,结果表明空间矢量脉宽调制直接转矩控制能够有效地减少电动机转矩和磁链的脉动。     

基于自适应状态观测器的异步电机无速度传感器矢量控制系统

异步电机无速度传感器矢量控制系统是目前研究的热点,本文采用一种闭环磁链观测器,即自适应状态观测器对转子磁链进行观测,与传统开环电压、电流模型相比,观测效果更好。在转子磁链观测的基础上,采用PI型自适应律,对转速进行了辨识。最后,通过Matlab仿真验证了本文给出的异步电机无速度传感器矢量控制系统的可行性,仿真结果表明该系统具有较好的动、静态性能,并具有一定的抗干扰能力。     

电流驱动按定子和气隙磁链定向的矢量控制

按转子磁链定向的矢量控制系统与转子参数有关,使得交流调速系统的性能受到影响。本文采用电流输出控制型逆变器,按定子磁链和气隙磁链定向的矢量控制,推导解耦控制方程,附加去耦项,实现系统的彻底解耦控制,磁链检测和转矩检测不含转子参数,仿真结果表明,新系统提高了磁场定向的准确性和解耦能力,改善闭环控制的动态性能和鲁棒性。     

基于全阶观测器的异步电动机矢量控制系统

磁链观测一直是异步电机无速度矢量控制的难点,本文以异步电动机本身为参考模型,设计了全阶观测器的可调模型来估算异步电机的磁链和速度。利用Matlab软件构造了按转子磁场定向的矢量控制系统的仿真模型,采用全阶观测器的方法在逆变器仿真平台和实验平台上实现了异步机的无速度矢量控制。通过仿真和试验验证了模型的正确性,结果表明所建立的调速系统具有良好的动态性能。     

基于MRAS的永磁同步电机直接转矩控制系统的研究

研究了一种基于模型参考自适应无速度传感器的永磁同步电机直接转矩控制系统:将永磁同步电机的磁链模型作为参考模型,估算的定子磁链模型作为可调模型,设计了自适应定律对电机的转速与定子电阻同时进行跟踪辨识,使用空间电压矢量调制技术组成了永磁同步电机无速度传感器直接转矩控制系统。仿真实验结果表明该系统获得了近似圆形的定子磁链,在转速与转矩变化时均能准确的估算出电机转速,具有良好的动、静态性能。     

DTFC-SVM motion-sensorless control of a PM-assisted reluctance synchronous machine as starter-alternator for hybrid electric vehicles

Permanent magnet-assisted reluctance synchronous machine (PM-RSM) starter alternator systems are credited with good performance for wide speed range in hybrid electric vehicles. This paper proposes a motion-sensorless motor/generator control of PM-RSM from zero speed up to maximum speed, using direct torque and flux control with space vector modulation. A quasioptimal stator flux reference with a flux versus torque functional is proposed. A stator flux observer in wide speed range uses combined voltage-current models for low speeds, and only the voltage model for medium to high speeds, both in proportional-integral closed loop. A novel rotor speed and position observer with a fusion strategy employs signal injection and only one D-module vector filter in stator reference for low speed, combined with a speed observer from the stator flux vector estimation-for medium-high speed. The proposed system is introduced piece by piece and then implemented on a dSpace 1103 control board with a 350-A metal-oxide-semiconductor field-effect transistor-pulse-width modulation converter connected to a 42-Vdc, 55-Ah battery, and a 140-Nm peak torque PM-RSM. Extensive experimental results from very low speed to high speed, regarding observers and drive responses, including artificial loading (motoring and generating), seem very encouraging for future starter-alternator systems.     

Online Stator and Rotor Resistance Estimation Scheme Using Artificial Neural Networks for Vector Controlled Speed Sensorless Induction Motor Drive

This paper presents a new method of online estimation for the stator and rotor resistances of the induction motor for speed sensorless indirect vector controlled drives, using artificial neural networks. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The rotor speed is synthesized from the induction motor state equations. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations for variations in the stator and rotor resistances from their nominal values. Both resistances are estimated experimentally, using the proposed neural network in a vector controlled induction motor drive. Data on tracking performances of these estimators are presented. With this speed sensorless approach, the rotor resistance estimation was made insensitive to the stator resistance variations both in simulation and experiment. The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive     

Sensorless DTC-SVM for Induction Motor Driven by a Matrix Converter Using a Parameter Estimation Strategy

This paper presents a new direct torque controlled space vector modulated method to improve the sensorless performance of matrix converter drives using a parameter estimation scheme. The flux and torque error are geometrically combined in a new flux leakage vector to make a stator command voltage vector in a deadbeat manner. A new sensorless method of estimating the rotor speed, flux, stator resistance, and rotor resistance is derived and verified with experimental results. Common terms in the error dynamics are utilized to find a simpler error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming the rotor speed is constant. The proposed adaptive schemes are determined so that the whole system is stable in the sense of Lyapunov. The effectiveness of the proposed algorithm is verified by experiments.     

Stator flux based space-vector modulation and closed loop control of the stator flux vector in overmodulation into six-step mode

This paper presents closed loop control of stator flux vector in a wide operating range that can be used in torque control. A predictive control achieves zero phase error at constant switching frequency. Space vector modulation based on stator flux error vector is used to achieve control of stator flux over the entire range including overmodulation and six-step. During dynamics the fastest possible flux vector change is employed similar to the direct torque control. Experimental results are provided for a wide speed range and effect of parameter variation is studied.     

An improved stator flux estimation for speed sensorless stator fluxorientation control of induction motors

This paper proposes a programmable low pass filter (LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the DC drift problem associated with a pure integrator and a LPF. The pole of the programmable LPF is located far from the origin in order to decrease the time constant with the increasing speed. In addition, the programmable LPF has a phase/gain compensator to estimate exactly stator flux in a wide speed range. Consequently, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range. The validity of the proposed programmable LPF is verified by speed sensorless vector control of a 2.2 kW three-phase induction motor     

基于模型参考自适应系统的感应电机控制

采用模型参考自适应法设计了无速度传感器矢量观测器。现以电压模型为参考模型,电流模型为可调模型,推算出速度信息,计算输出控制信号,实现了对感应电机的精确控制;通过Matlab／Simulink对其进行仿真、验证,结果表明,该系统对定子磁链观测精度高,速度估计准确,改善了电机的控制特性。     

双馈风力发电机功率解耦控制的研究

介绍双馈风力发电机的基本原理,利用矢量控制并结合定子磁场定向的矢量控制,建立基于Matlab的双闭环控制系统仿真模型。为了更为准确地实现定子磁场定向并考虑到定子绕组电阻对磁场定向的影响,采用改进型的定予磁链观测模型。通过仿真验证了采用改进型定子磁场定向的双馈风力发电控制系统,实现了有功功率和无功功率解耦。     

Speed-sensorless sliding-mode torque control of an induction motor

Novel induction motor control optimizing both torque response and efficiency is proposed in the paper. The main contribution of the paper is a new structure of rotor flux observer aimed at the speed-sensorless operation of an induction machine servo drive at both low and high speed, where rapid speed changes can occur. The control differs from the conventional field-oriented control. Stator and rotor flux in stator fixed coordinates are controlled instead of the stator current components in rotor field coordinates i_sd and i_sq. In principle, the proposed method is based on driving the stator flux toward the reference stator flux vector defined by the input command, which are the reference torque and the reference rotor flux. The magnitude and orientation angle of the rotor flux of the induction motor are determined by the output of the closed-loop rotor flux observer based on sliding-mode control and Lyapunov theory. Simulations and experimental tests are provided to evaluate the consistency and performance of the proposed control technique